This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Enzymes are essential to a wide range of industrial processes. As biocatalysts, they play a key role in producing active pharmaceutical ingredients, specialty chemicals and ingredients for cosmetics, besides being vital to the food industry.
Enzymes allow many chemical reactions to occur under milder conditions, thereby saving energy and making existing processes more efficient and environmentally friendly. Molecular biology, genetic engineering and bioinformatics can be used to optimize enzymes for industrial applications. Targeted changes to an enzyme's genetic blueprint can make it work faster, keep it reliable even under demanding process conditions or help it control chemical reactions with greater precision.
Modern computational methods and artificial intelligence can support this process by helping identify suitable enzyme variants more quickly. Nevertheless, developing custom enzymes remains a resource-intensive process. The complex relationships between genetic sequence, three-dimensional structure and enzymatic function make accurate predictions difficult.
One major bottleneck is the lack of experimental data on how genetic changes affect enzyme function. This is where the ZenBio project comes in. Researchers at the Fraunhofer Institute for Cell Therapy and Immunology, Branch Bio-analytics and Bioprocesses IZI-BB in Potsdam are developing an automated platform that uses cell-free protein synthesis to generate large volumes of sequence-function data for AI-assisted enzyme design.
This will accelerate the process of producing and analyzing enzyme variants and developing them into high-performance biocatalysts for industrial applications. The project addresses the specific demands of industrial processes. "Enzymes are naturally adapted to the conditions in the organisms where they occur," explains Simon Krebs, a biotechnologist at Fraunhofer IZI-BB.
"Industrial processes, on the other hand, often impose very different demands. Enzymes may need to withstand higher temperatures, altered pH levels or organic solvents. In the ZenBio project, we are tailoring enzymes to these applications, thereby unlocking new manufacturing processes that are difficult to achieve using conventional chemistry." "AI can only learn from what has been measured experimentally," explains Benedikt Dechamps, an industrial engineer at Fraunhofer IZI-BB.
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